ABSTRACT
The term virtualization primarily focuses on the process of replacement of physical devices with virtual devices. In such cases applications along with servers and workstations can be virtualized. This confines security to operating systems as it is aimed towards complete reproduction of networks to support logical devices as well as logical network services. Generally there is the provision to link data with clients allocating storage in the cloud. To achieve this it is essential to enhance the efficiency of the system as it is based on demand service implemented through datacenters provisioning the resources in the cloud. It is also the responsibility of the virtual machine monitor to judge the resources implementing the time-sharing mechanisms. During this process virtualization in storage has the vital role as the implementation in this case is done through storage area networks. It initiates abstraction mechanisms among the storage and ongoing applications in the machines concerning processed data and metadata. From an educational point of view, these applications have a unique potential to enhance efficiency at minimal cost with the capacity to focus on research initiatives and global learning. But still there are so many factors to consider while implementing these techniques in the proper direction. In this work, the prioritization is given to the potentiality of the data associated with the virtual machines using particle swarm optimization techniques to obtain the parametric constraints and cost of the swarm variables.
